节点定位在湖泊监测中的优化研究
发布时间：2018-07-22 12:56
【摘要】：无线传感网湖泊监测中,节点位置在一定范围内随机漂移,导致定位精度需持续修正并提高精度。提出最小误差二次定位估计算法,初始时在网络中设定两组配置有GPS的3个信标节点,利用三边测量法对未知节点进行定位,通过分析RSSI测距误差求出中心点,建立两组测量坐标进行定位修正,再使用跳距对两组坐标测量结果进行加权估计,获得优化后的最小误差节点定位。对比常规的三边测量法和FTL算法,通过仿真验证,该算法在湖泊监测中能有效地减小定位误差。
[Abstract]:In the lake monitoring of wireless sensor networks, the location of nodes is drifting randomly in a certain range, which leads to the continuous correction of the positioning accuracy and the improvement of accuracy. A minimum error two position estimation algorithm is proposed. In the initial time, two sets of beacon nodes with GPS are set in the network, and the three side measurement method is used to locate the unknown nodes, and the RSSI measurement is analyzed by analysis. The center point is obtained from the distance error, two sets of measurement coordinates are set up to fix the positioning correction, and then the weighted estimation of the results of the two sets of coordinate measurement is carried out with the jump distance, and the minimum error node location after the optimization is obtained. Compared with the conventional three edge measurement and FTL algorithm, the algorithm can effectively reduce the location error in the lake monitoring.
【作者单位】： 昆明理工大学信息工程与自动化学院;
【基金】：国家自然科学基金(No.61262040)
【分类号】：TN929.5;TP212.9
本文编号：2137533
[Abstract]:In the lake monitoring of wireless sensor networks, the location of nodes is drifting randomly in a certain range, which leads to the continuous correction of the positioning accuracy and the improvement of accuracy. A minimum error two position estimation algorithm is proposed. In the initial time, two sets of beacon nodes with GPS are set in the network, and the three side measurement method is used to locate the unknown nodes, and the RSSI measurement is analyzed by analysis. The center point is obtained from the distance error, two sets of measurement coordinates are set up to fix the positioning correction, and then the weighted estimation of the results of the two sets of coordinate measurement is carried out with the jump distance, and the minimum error node location after the optimization is obtained. Compared with the conventional three edge measurement and FTL algorithm, the algorithm can effectively reduce the location error in the lake monitoring.
【作者单位】： 昆明理工大学信息工程与自动化学院;
【基金】：国家自然科学基金(No.61262040)
【分类号】：TN929.5;TP212.9
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